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OBJECTIVESThis study aimed to to investigate the possibility of using the ClinProt technique to find diagnostic markers that are able to better discriminate healthy subjects from patients affected by endometriosis(EMs). Endometriosis is a common gynecological disease. Biomakers for early detection, prognosis, follow-up, and differential diagnosis of Ems are needed in daily clinical practice.METHODSPeritoneal fluid and urine samples were analyzed by the ClinProt and MALDI-ToF technique. We combined the automated high through put MALDI-TOF measurements and LC-MS/MS to identify the different proteins.RESULTSAfter comparing the peritoneal fluid protein mass spectra of39patients with34controls,18differently expressed potential biomarkers (P<0.01) were identified. Using ClinproTool software, we established GA algorithm.When using the a cluster of five signals (m/z=4458.23,2379.3,8519.94,6376.99,6190.27) to classify the samples, the sensitivity for diagnosing endometriosis was88.5%, specificity was88.5%.Urine samples from30patients and31controls were also analyszed by MALDI-TOF. Using GA algorithm, The combination of five markers (m/z=1433.98,1599.48,2085.61,6798.07,3217.29) lead to an improvement in diagnostic efficacy, with specificity and sensitivity of95.7%and96.7%, respectively.Com bind ing the MALDI-TOF/TOF with LC-MS/MS, we identified the proteins as collagen precursor.CONCLUSIONSThese results may be useful to set up new diagnostic or prognostic tools.
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